What is demand-driven MRP (DDMRP)?
DDMRP is an approach to material control and replenishment that improves on traditional MRP by making it sensitive to real-time fluctuations in demand.
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Overview of demand-driven MRP
Material requirements planning (MRP) has been the backbone of manufacturing software systems for half a century. MRP is the calculation engine that specifies which materials and parts to order, how many of each are required, when they will be needed, and when activity must begin to complete the work so products are ready by the forecasted completion date.
Traditional MRP is inherently forecast-driven. However, the one thing we know about forecasts is that because they are based on past activity, they are not always accurate in predicting the future. We may have some limited control over variability through procedural discipline, robust quality processes, reliable supplier partners, and other factors, but some uncertainty will remain. There will be surprises… and shortages.
Today’s supply chain—with greater volatility, uncertainty, complexity, and ambiguity—requires additional planning capabilities that are sensitive to real-time fluctuations in demand. This is where demand-driven MRP (DDMRP) comes in.
Meaning of DDMRP
DDMRP is the acronym for demand-driven material requirements planning (MRP), an approach to material control and replenishment that improves on the functionality of traditional MRP. Because DDMRP is demand driven, it is by definition more sensitive and responsive to the variations in demand and supply that can cause shortages, production disruptions, and chaos in manufacturing facilities.
DDMRP, also referred to as demand-driven replenishment, is an optional extension of MRP, not a replacement. For many manufacturers, MRP is sufficient; however, DDMRP helps it to work better, especially in a volatile environment.
How does traditional MRP work?
Traditional MRP does a good job of planning the materials and resources needed to build a product, provided the forecast is accurate and there are no unexpected changes to demand within the total lead time allocated to build the product. Unfortunately, in a dynamic environment, things change quickly.
When demand fluctuates, MRP’s way of reducing risk is to stage extra “just in case” stock throughout the supply chain using a number of assumptions and formulae. When the unexpected does occur, some of that extra buffer stock can therefore be used. The extra stock does prevent shortages, but only some of them; shortages may still occur. And carrying extra stock ties up cash and space.
Also, when MRP detects an impending shortage—when buffer stock is being consumed—it will issue alerts to users to expedite replacements for that stock, triggering a series of manual operations.
The real problem is variability caused by forecast inaccuracy and supply chain variations, including late receipts, late order completions, excessive scrap, quality issues, and inaccurate records, for example. While manufacturers realise that variability cannot be altogether eliminated, they want a way to reduce excess stock and experience fewer shortages. DDMRP offers an enhancement to traditional MRP that does exactly that.
How does demand-driven MRP work?
While MRP is a “push” technique that pushes stock into the system based on the forecasted need, DDMRP operates differently.
DDMRP removes variability from the equation by using “pull” for materials in a demand-driven approach. Instead of relying on forecast accuracy—and buffering for fluctuations in demand and supply—DDMRP tracks actual usage and manages replenishment through a straightforward visual system. Buffer stock is only used to ensure the availability of key items that are considered to be of strategic importance. With the use of DDMRP, there is less stock overall and fewer shortages.
DDMRP is structured around a methodology that can best be described as “position, protect, and pull.”
Diagram of the DDMRP process.
- Position: Bills of materials are examined to identify strategic items—materials or components—at critical points within the structures. In an adaptation of the Theory of Constraints method, in which critical resources known as “constraints” determine production limitations, these key materials must be the focus of control above all other components.
- Protect: Availability of these critical items is also ensured by using stock as a buffer. However, this buffer stock is not utilised as part of the initial MRP planning formula; instead, it is replenished dynamically as required.
- Pull: Buffer stock is managed through an innovative pull technique that continually monitors stock levels and uses visual cues to maintain the buffer within a specified range.
Here are the detailed steps in the process:
- Identify the strategic items to manage through DDMRP.
- Establish the target stock (buffer) level and parameters (resupply trigger zones).
- Replenish using the pull signals represented by the coloured indicators.
- Plan using functions within DDMRP.
- Collaborate with supply chain partners using the replenishment zones/triggers to execute the plan.
As you can see, DDMRP users pull controlled stock at strategic positions to protect the production schedule by avoiding shortages. DDMRP also requires less stock because only strategic items are buffered, and the pull technique ensures the right amount of that stock is maintained for those strategic items. The visible execution cues complete a simple and dynamic replenishment process that is easy to implement and maintain. MRP is still part of the picture, however, as it maintains its normal function for non-strategic items and coordinates with DDMRP in the planning process.
DDMRP vs. MRP
Here’s a summary of the differences between DDRMP and MRP that illustrate their complementary relationship:
How did DDMRP software evolve?
DDMRP was created and refined by some of the sharpest and most innovative thinkers in traditional manufacturing management, lean manufacturing, and the Theory of Constraints. After proving and refining the process at manufacturing locations across the globe, the team formed the Demand Driven Institute with the following aims:
- Spread the word about DDMRP.
- Educate and certify manufacturing professionals in its implementation and use.
- Work with software developers to integrate DDMRP into their ERP products.
- Validate that the functionality complies with DDMRP guidelines and standards.
Get started with DDMRP software
Companies adopt DDMRP software in one of two ways: as part of an ERP system or as part of a supply chain planning solution.
The DDMRP functionality in a modern cloud ERP system (such as SAP Cloud ERP) is robust enough to meet the needs of most small businesses and mid-market companies—however, enterprises with multiple plants and suppliers may require more advanced capabilities. In these cases, a cloud-based, best-of-breed supply chain planning solution (such as SAP Integrated Business Planning for Supply Chain) is required. These solutions typically integrate with ERP and offer other aspects of planning, such as sales and operations planning (S&OP), demand forecasting, stock planning, and “what-if” scenario analysis.
Whether you implement DDMRP via ERP or a supply chain planning solution, seek features that utilise AI, machine learning, real-time visualisation, and alerts to help you respond more swiftly to market and business unpredictability.
Predicting ever-changing demand
Learn how the chemicals supplier BYK-Chemie improved its data accuracy and transparency to enable precise demand planning.
FAQs
AI enhances DDMRP by making supply chain planning smarter and more adaptive. AI improves demand forecasting through advanced analytics, enabling businesses to sense market changes in real time. It also optimises buffer management by dynamically adjusting inventory levels based on variability and lead times. Additionally, AI provides predictive insights to anticipate supply chain disruptions and automates restocking decisions for a faster response.
AI in DDMRP benefits include higher forecast accuracy, inventory optimisation, proactive risk management, and reduced costs through automation and real-time decision-making. By integrating AI with DDMRP, companies can achieve a more resilient, efficient, and demand-driven supply chain.
Unlike traditional MRP, which relies heavily on forecasts and fixed lead times, DDMRP uses real-time demand data and dynamic buffers to adjust supply. This reduces the bullwhip effect, improves responsiveness, and minimises excess stock.
DDMRP can complement or replace traditional MRP depending on your business needs. Many companies integrate DDMRP into their existing ERP systems to enhance planning accuracy and agility.
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